VyContext enforces your IP-development standards automatically inside your IDE. Faster onboarding, consistent code, fewer late-stage integration failures.
Requirements: VyContext requires installing the IDE extension (VS Code or Cursor) and a GitHub or Google account login — even for the free tier. This ensures secure account association, delivers your context, and enforces subscription limits.
Installation: VS Code users can install from the VS Code Marketplace. Cursor users can install from Open VSX Registry.
Click "Register" at the bottom of the login dialog
VyContext makes your methodology system-enforced, not individually remembered. Reduce onboarding time, increase IP reuse, prevent costly late-stage integration failures, and transform your engineering organization into a continuous innovation engine — safely.
Time to value
Onboarding time (vs. months)
Reduction in review time
Methodology compliance
Common challenges in silicon IP development — and how VyContext solves them.
| Problem | VyContext Solution | Outcome |
|---|---|---|
| New engineers take months to onboard. They ask teammates for examples, search through tribal knowledge, and make mistakes that delay projects. | AI IDE-native templates and metadata-driven catalogs provide instant access to standardized patterns. No searching, no asking — everything is right in your AI IDE. | Onboarding time cut from months to days — instant access to your team's best practices. |
| AI tools generate non-compliant code. Engineers waste time fixing naming conventions, directory structures, and methodology violations in code reviews. | Automatic methodology enforcement in IDE ensures AI-generated code adheres to your rules — naming, directory structures, checklists, package formats. | Reduce review cycles by 30% — AI-generated code is compliant from the start. |
| IP reuse is tribal knowledge. Teams duplicate work, miss existing IP blocks, and face costly late-stage integration failures when incompatible IP is integrated. | Metadata-driven discovery & reuse with catalog integration. Find compatible IP blocks instantly, understand dependencies, and ensure consistent standards across teams and vendors. | 100% methodology compliance — prevent costly integration failures before they happen. |
| Compliance issues and security concerns prevent teams from using AI tools. Data residency requirements, audit trails, and enterprise security standards block adoption. | HTTPS GET only — no data sent to Vyges. Works with any LLM (AWS Bedrock, Azure OpenAI, on-prem). VPC/on-prem data residency by default. Google/GitHub login or Enterprise SSO. | Secure & compliant workflow — use AI tools without compromising security or compliance standards. |
Benefits you get, features that deliver them.
Benefit: New engineers become productive immediately, not after months of training.
Features: IDE-native templates, metadata-driven catalogs, standardized patterns available instantly in your IDE.
Benefit: Consistent IP standards across teams & vendors — no more integration surprises.
Features: Enforced naming, directory structures, checklists, package formats. Automatic methodology enforcement in IDE.
Benefit: Use AI tools without compromising security or compliance standards.
Features: HTTPS GET only; no data sent to Vyges. Works with any LLM (AWS Bedrock, Azure OpenAI, on-prem). VPC/on-prem data residency by default.
Benefit: Out-of-box context for silicon development — no manual setup or configuration.
Features: RTL & SoC design patterns, verification (UVM, cocotb, SVAs), physical implementation (UPF, timing closure), metadata-driven discovery & reuse.
Benefit: Works with your existing infrastructure and tools — no vendor lock-in.
Features: Works with AWS Bedrock, Azure OpenAI, on-prem LLMs. VS Code, Cursor, JetBrains support. No manual prompting or external docs.
Plans are continuously updated to address customer needs. Contact us for enterprise-specific plans and customizations.
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See what early adopters are saying about VyContext
"I used the Vyges AI platform to generate RTL for a Stanford-based 32-bit RISC processor with a 5-stage pipeline, interrupts, branch prediction, and later a full 32-bit multiplier with hazard detection. I described the spec entirely in plain English, and the platform asked for clarifications only when needed.
Vyges generated the full repository—architecture docs, RTL, testbench, and files—cleanly organized and cross-referenced. The RTL quality was excellent: modular, readable, and comparable to what an expert team would build. Even the gate-count estimate (TSMC 22 nm) matched our prior silicon results.
Overall, Vyges dramatically accelerates chip-design productivity if you know what you want."
"I used the Vyges AI-based platform to design RTL for a Stanford-derived 32-bit RISC processor. The initial spec included a 5-stage pipeline, aligned memory accesses, NMI + four interrupts, and simple branch prediction. We later expanded the spec to include a complex 32-bit multiplier with overflow, pipeline stalls, and hazard-detection logic.
I wrote the entire spec in plain English. The platform only asked for clarification where needed, and the whole process took minutes. Vyges then generated a complete project repository—architecture docs, RTL, testbench, collateral—neatly structured and cross-referenced.
The RTL quality genuinely surprised me. It was modular, logically partitioned, and well-commented—exactly the kind of work you'd expect from a highly experienced engineer. Even the gate-level estimate for a 22 nm TSMC node was accurate (≈50k gates, including a 10k-gate multiplier), matching our past silicon.
Overall, the Vyges platform is impressive. With a clear idea of what you want to build, it massively boosts chip-design productivity."
Kumar Hebbalalu
Silicon Expert
VyContext transforms your engineering organization into a continuous, compliant innovation engine — enabling AI-powered development inside your IDE without compromising methodology, quality, or security.